The use of touch-sensitive surfaces as input devices for computers and other electronic computing devices has increased significantly in recent years. Exemplary touch-sensitive surfaces include touch pads and touch screen displays. Such surfaces are widely used to manipulate user interface objects within an electronic canvas through touch-based gestural command inputs.
But existing methods for touch-based gestural command input within electronic canvases are cumbersome and inefficient, creating a significant cognitive burden on a user. For example, when a device supports a rich collection of input gestures for a touch-sensitive surface, it can be challenging for a user to distinguish between physically similar gestures, recall the different gestures that are available for particular operations, or transition between gestures. In addition, existing methods take longer than necessary, thereby wasting energy. This latter consideration is particularly important in battery-operated devices.
As a result, there is a need for improved gestures and gesture processing techniques that allow a user to employ a rich set of gestures for a touch-sensitive surface with increased efficiency and ease of recall. Such methods and interfaces reduce the cognitive burden on a user and produce a more efficient human-machine interface. For battery-operated computing devices, such methods and interfaces conserve power and increase the time between battery charges.